Introduction to Unmanned Vehicle

Systems

Fall 2015

Dr. Brian Huff, IMSE Dept.

Why Offer This Course?

Offer at true Multi-Disciplinary Educational Experience

Introduce students to the exciting field of Unmanned Vehicle Systems Development.

To have a good reason to learn about cool technology from the perspective of multiple engineering disciplines.

To provide a foundation for both the Undergraduate and Graduate Unmanned Vehicle Systems Certificates.

What Course Is This?

CSE 4378 EE 4378 IE 4378 MAE 4378 AE 5378 CSE 5383 EE 6321

IE 5378 ME 5378

Introduction to Unmanned Vehicle Systems

Who will be teaching the Course?

Dr. Atilla Dogan, MAE Dr. Brian Huff, IMSE Dr. Manfred Huber, CSE Dr. Kamesh Subbarao, MAE Dr. Dan Popa, EE

Lecture Overview

Class Syllabus (Highlights) UVS Certificate Programs UVS History Types of UVS UVS Component Technologies

Syllabus – Learning Objective

Provide students with a general overview of technologies and engineering methods used to develop and deploy Unmanned Vehicle Systems.

Provide a team-taught class experience. Present materials that would typically fall outside the

student’s main area of study. Challenge the student to explore the inherently multi-

disciplinary nature of today’s complex engineered systems.

This course is the first course of a common two course sequence that forms the foundation of an Undergraduate and Graduate UVS Certificate program.

Syllabus – Course Content

Introduction to UVS (Unmanned Vehicle Systems): UAS (Unmanned Aircraft Systems)

UGS (Unmanned Ground System)

UMS (Unmanned Maritime System)

Their history, missions, and capabilities

UVS types, configurations and subsystems

The disciplines needed for UVS development and operation.

By the end of the course, you should be able to: Describe the common types, missions and roles of

Unmanned Vehicle Systems

Identify and list the common subsystems and technologies deployed in UVS

Use the Matlab/Simulink toolsets to model unmanned systems

Discuss the various types of sensors used within UVS and describe suitable sensor fusion methods

Describe the common methods used by UVS to perform Guidance, Navigation, & Control functions

Describe the approaches and technologies used to create UVS man/machine interfaces

Syllabus – Textbooks & Course Materials

The is no required Text for this course. Notes and supplemental materials will be provided by the course instructors.

Syllabus – Major Assignments, Tests, & Grading Five Homework Assignments

25% Test 1 – In class test

20% Take-Home Project

15% Test 2 – In class test

30% Class Participation/Pop Quizzes 10%

The following scale will be used to assign class grades: 

A 90% - 100%B 80% - 89%C 70% - 79%D 60% - 69%F less than 60%

Syllabus – Emergency Exit Procedures

Exit out of the front of the Auditorium

Turn right as you enter the atrium

Doorway out of the building is directly in front of you

Exiting NH 105

UVS Certificate Programs Offered at both the Undergraduate and

Graduate levels Offered by the CSE, EE, IMSE, & MAE

Departments Certificate program requires a total of 15 hours

of course work: Six hours of core curriculum that is common

across all programs Nine hours chosen from a portfolio of classes

identified in each program

UVS Certificate Programs

Common Courses

Introductory course provides students with a background in UVS and prepares them for the eventual teamwork necessary for the final course project

Final course in program is a 3-hour project-based course that involves the design and construction of a functional UVS system or component involving teamwork and collaborative effort between students from participating departments

Why have Autonomous/Unmanned Systems become so popular?

Technological Reasons The rapid increase in computing power Significant miniaturization of enabling technologies Significant cost reductions in enabling system

components Sociological / Economic Drivers

The reduction in risk and cost associated with using humans to perform Dull, Dirty, and Dangerous Jobs

A reduction in tolerance for the loss of life in Military Operations

Potential to do productive work

Future Computing Power

Moore’s Law 2019 $1000 computer has

power of human brain 2029 $1000 computer has

power of 1000 human brains

2049 $1000 computer has power of human race

Low Cost, High Power Computing is not a Bottleneck

IEEE Spectrum, Richard D. Jones - Boeing Phantom Works

Future CommunicationBy 2020 We will have Ubiquitous High

Bandwidth Communication Today - WiFi (vehicle to vehicle) Soon - WiMax (30 km range)

above metropolitan areas

Edholm’s Law (IEEE)

Bandwidth growing Faster then Moore’s Law (doubling every 12 months)

Soon (2015?) Nomadic (wireless) will Exceed Wireline

IEEE Spectrum, Richard D. Jones - Boeing Phantom Works

The Senate Armed Services Committee’s Demand for Unmanned Systems

February 2000, Sen. John Warner (R-VA), Chairman of the Senate Armed Services Committee, publicly stated his desire to see one-third of military aircraft designed to strike deep within enemy territory would be unmanned by 2010 and one-third of ground combat vehicles would be driverless by 2015.

In the Senate Armed Service Committee’s version of the 2007 Defense budget they state:

“The Secretary of Defense shall… develop a policy applicable throughout the Department of Defense on research, development, test, and evaluation, procurement, and operation of unmanned systems [which] shall include the… preference for joint unmanned systems in acquisition programs for new systems, including a requirement under any such program for the development of a manned system for a certification that an unmanned system is incapable of meeting program requirements”

Demand from Commercial Companies

UVS History

The Defeat of the Spanish Armada 1588 –The English sent eight burning ships into the crowded harbor at Calais. The panicked Spanish ships were forced to cut their anchors and sail out to sea to avoid catching fire. The disorganized fleet, completely out of formation, was attacked by the English off Gravelines at dawn. In a decisive battle, the superior English guns won the day.

UVS History

The development of unmanned vehicles for military use predates the development of industrial automation.

In 1849 unmanned balloons loaded with explosives were used against the city of Venice by Austrian forces.

During World War I “aerial torpedoes” were developed using radio control techniques and early gyroscopes.

UVS History

The Kettering Bug was first flown in 1918.

Range: 75 miles Speed: 120 mph Payload: 180 lbs of

explosives Production: 45 units

http://en.wikipedia.org/wiki/Kettering_Bug

UVS History

The Radioplane Company produced nearly fifteen thousand target dones during WWII

Radio Controlled B-17 and B-24 bombers also saw limited combat use during World War II

UVS History

Germany developed radio and wire controlled vehicles in World War II

The vehicles were used for mine clearance, explosive charge carriers, and anti-tank weapons

UVS History

The German Goliath tracked mine, also known as the beetle tank by the Allies. Size: 4’x2’x1’ Payload: 165-220 lbs of

high explosives Uses: destroying tanks,

demolition of buildings and bridges, disrupting dense infantry formations

25

Less Familiar Systems Hard at Work

Classes of UxVs

Unmanned Aerial Vehicles (UAV) Unmanned Ground Vehicles (UGV) Unmanned (water) Surface Vehicles (USV) Unmanned Underwater Vehicles (UUV) Unmanned Munitions (UM) Unattended Ground Sensors (UGS) Unmanned Orbital Vehicles (UOV)* Unmanned Cyber Vehicles (UCV)* Unmanned Interbody Vehicles (UIV)*

* Bowen, David G., MacKenzie, Scott C., Autonomous Collaborative Unmanned Vehicles: Technical Drivers and Constraints, Defense R&D Canada, Contract Report DRDC CR-2003-003, September 2003

UxV Capability Classes

Teleoperated Vehicles(“Searcher”)

Semiautonomous Preceder/Follower

(“Donkey”)

Platform-Centric Autonomous Vehicle

(“Wingman”)

Network-Centric Autonomous Vehicle

(“Hunter-Killer” Teams)

“Searcher” UxV Characteristics

Teleoperated Vehicles Human operator controls the vehicle at a distance Operator’s information about the vehicle’s environment and state

depends critically on: sensors that acquire information, communications links, and display technologies to allow the operator visualize the environment and access the performance of the vehicle.

Human operator is responsible for the command and tasking functions of the vehicle

Have no onboard terrain reasoning or military maneuvering capability Applications:

Mine detection/clearing, soldier-portable reconnaissance/surveillance, UXO/IED, Search and Rescue

Whats over hill or around the corner?

“Donkey” UxV Characteristics

Semiautonomous Preceder/Follower Vehicles Characterized by limits on the scope of autonomous mobility Designed to follow markers (“breadcrumbs”) left by a “leader” Would use some cognitive process to select best route from marker to

marker through a “known environment” previously traversed by the leader

Sensor suite is more complex than found on the “Searcher” Preceder Donkey must: have sufficient autonomy to move in advance of

its controller, support complex terrain reasoning to select the best route Applications:

Carry supplies, support road-traversing convoy mode, support forward reconnaissance, surveillance and target assessment (RSTA) 1 – 5 km in advance of controller, support supply prepositioning, a Preceder could lead less capable followers

Be the soldier’s “mule”

“Wingman” UxV Characteristics

Platform-Centric Autonomous Vehicles The UxV, once given orders for a complex mission, can accomplish them

without being told how. Can transverse between two waypoints (a few kilometers to a hundred

kilometers apart) with no help along the way by a human operator (A-to-B autonomy). Must include same environmental conditions (terrain, weather, etc.) as would be operated in by manned vehicles.

Must be able to carry out its mission in a hostile environment with the same survivability and self-defense as manned systems.

Capable of identifying friends, foes, and noncombatants (IFFN) Must carry adequate self-defense systems suitable for its operational

environment and anticipated threats. Capable of refueling itself from unmanned prepositioned fuel supplies or

rendezvous with a fuel supply vehicle (manned or unmanned).

“Wingman” UxV Characteristics (continued)

Platform-Centric Autonomous Vehicles Have sufficient reliability and robustness to withstand the common

hazards and mishaps encountered in the course of typical operations. Have the cognitive processing capabilities to support tactical maneuver

and self-protection/self-defense behavior. Applications:

Support the conventional “work as a team” model based on the roles of “Section Leader” and “Wingman”. The Section Leader tells the Wingman (or Wingmen) what to do, but not how to do it. A Section Leader and a Wingman would then interact to faction as a team. This model would require the autonomous “Wingman” UxV to have the cognitive processes and mission knowledge required to perform tasks without instruction or support from the Section Leader.

“Cover my back little buddy”

“Hunter-Killer” UxV Team Characteristics

Teams of Network-Centric Autonomous Vehicles Must be competent as independent nodes in a network-centric

hierarchical, non-deterministic, command and control environment. The Network-Centric UxV can have “many masters” and must have the

ability to arbitrate conflicting requests for service. Must support the coordination between ten to one hundred UxV team

members to accomplish a complex mission. Must have the ability to request and verify “go / no-go” authorization from higher-level command and control entities.

“Tell us what to do and get out of the way…”

UVS Technology AreasBehaviors &

Skills

NavigationPerception

PlanningLearning / Adaptation

Autonomous Behavior

Human-Robot Interaction

Health Maintenance

Power

Mobility

Communications

UxV Systems

UVS Enabling Technologies

Human-Robot Interaction (HRI) Covers issues of how intelligent agents work together in a system.

Extends beyond conventional human-computer interface (HCI) issues.

Attempts to address how humans will interact with multiple robots (especially under stressful conditions).

Considers the dynamic allocation of tasks between humans and robots based on situational context in an effort avoid information overload and improve workload balance.

Support for Teaming has a large impact on HRI Requirements

Teamwork Architectures – optimal organization of teams

Task Allocation – the allocation of tasks between human and robot agents based on the non-homogeneous capabilities of the team resources

UVS Enabling Technologies

Mobility

The ability of the vehicle to move about in a given operational environment.

Accessed in terms of the size and class of obstacle (both positive and negative) a vehicle can negotiate and still continue along its specific path and/or the modes of motion supported by the platform (e.g. vertical takeoff for UAV)

Increased mobility reduces the perception burden and lowers the potential need for human intervention.

Mobility Requirements must be driven by the application scenarios associated with a given UVS.

UVS Enabling Technologies

Communications The ability to communicate with an UVS will be required unless it will be

totally autonomous and accept no input from the outside world. (This is not a realistic or desirable characteristic)

UVS communication systems have a complex set of interdependent issues: Frequency, Bandwidth, Transmission Range, Interference, Power Consumption, Broadcast Power Constraints, Protocols, Encryption, Ontology, etc.

Not all communications modalities will work for all classes of UVS. UUV communications technologies are very different from those used in an air medium.

For some classes of UVS, particularly the Teleoperated platforms, the loss of a communications link can result in a mission critical failure resulting in the loss of the vehicle.

UVS Enabling Technologies

Power/Energy

This is critical issue, particularly for small UVS platforms, systems and applications that require long endurance, (a key advantage of using unmanned technologies), or in domains where fuel weight and volume have a significant impact on vehicle performance (e.g. UAV systems).

There are safety, cost, and compatibility issues.

Mission characteristics may directly impact power/energy related system requirements (e.g. the need for stealth operation)

A very large selection of power and energy options exist, each with a unique set of tradeoffs.

UVS Enabling Technologies

Health Maintenance This is another critical issue in unmanned systems because there is no

highly intelligent, omni-sensing, agent onboard to smell the smoke, hear the rattles, feel the vibrations, sense the heat, and realize that it might be a good idea to land the plane.

There are many types or sources of potential failure in systems as complex and technologically diverse as autonomous vehicles.

Every potential failure mode, symptom, cause, and remedy must be identified for the UxV system.

For each failure mode, a set of corresponding failure symptoms must be defined.

For each failure symptom and sensing technology must be identified that can reliability detect these symptoms.

UVS Enabling Technologies

Health Maintenance (continued)

Each sensor technology must be designed into the mechanical, electrical and controls subsystems of the vehicle.

For each Failure Mode that is identified, a failure mediation process must be defined.

The physical and logical infrastructure for performing these failure mediation processes must also be included in the system design.

Decision criteria must be developed to determine what levels of sensor input constitute the detection of a failure.

The computational burden associated with constantly checking the sensor inputs and testing them against the failure detection thresholds can potentially detract from the computing resources needed to perform the UxV’s primary mission.

UVS Enabling Technologies

Autonomous Behavior Technologies Autonomous Behavior is a key technology enabler because it provides the

automated perception and reasoning capabilities need to makeup for the loss of the highly intelligent, omni-sensing, agent (i.e. the human) that has now been excluded from the system design.

Autonomous behavior is enabled by the integration of a set of related technologies: Planning, Perception, Behavior & Skills, Navigation, and Learning/Adaptation.

These technologies are highly interdependent as is indicated in the following Autonomous Behavior Subsystem block diagram.

Behaviors & Skills

NavigationPerception

PlanningLearning / Adaptation

Autonomous Behavior

Autonomous Behavior Subsystems

Navigation

Learning

GPSIMU

OdometryLandmarks

Planning

Learning

Mission Planner

NavigatorPilot

Learning

Perception

World Map

Behaviors Learning

Sensors

Human Controller

Motor Commands

Autonomous Behavior Subsystems

Perception Subsystem

Takes data from sensors and develops a representation of the world around the UVS.

This representation of the UVS operational environment is referred to as the World Map.

The perception subsystem controls the sensor performance input parameters to optimize perception performance and can receive requests from the planner or behavior and skills subsystem to focus on a particular subset or region of inputs.

Autonomous Behavior Subsystems

Navigation Subsystem

Keeps track of the UVS current position and pose (roll, pitch, yaw) in an absolute coordinate system.

It provides a means to convert vehicle-centered sensor readings into an absolute frame of reference.

Will generally use a variety of independent means (GPS, IMU, Odometry) to determine location estimates.

These sensor inputs are frequently inconsistent and each have their own potential error causes and characteristics.

Sensor fusion methods and filtering techniques can then be used to improve the accuracy of our position/pose estimates.

Autonomous Behavior Subsystems

Planning Subsystem

Decomposes the high-level general task commands (e.g. move to location B) into a series of subtasks or functions like: determine current location (A), calculate distance and heading for a course from A to B, activate obstacle detection processes, turn onto heading from A to B, begin vehicle movement from A to B, monitor progress along vector between A and B, if vehicle encounters an obstacle or veers off course move around obstacle or turn back towards B, determine current location (C), and the process repeats.

More sophisticated planners might use predefined world map information to pre-plan a course from A to B.

Lower level controllers can be used to monitor system performance and effect the behavior of the system using performance data as feedback.

Autonomous Behavior Subsystems

Behavior and Skills Subsystem

A behavior is a combination of sensing and effecting into a atomic action. It can be innate, learned, or strictly a stimulus response.

A skill is a collection of behaviors needed to follow a plan or execute a complex task.

This Subsystem can combine inputs from Perception, Navigation, and Planning and translates them into motor commands for the UVS to move and accomplish work.

Autonomous Behavior Subsystems

Learning/Adaptation Subsystem

This function is frequently distributed within the various components of the autonomous behavior subsystem components.

The objective of these learning / adaptation functions is to improve system performance by analyzing historical system performance statistics and adjusting Autonomous Behavior Subsystem control factors.

It provides a mechanism for the system to become more robust over time.